Diagnostic of Heart Failure

ABSTRACT

The invention relates to a method for classifying a patient at risk for heart failure, wherein said method comprises the steps of (i) measuring the concentration of IGFBP2 in a sample obtained from said patient and (ii) comparing the concentration of IGFBP2 measured in step (i) to a control value derived from the concentration of IGFBP2 in samples from patients who are at particular stages of heart failure and/or to a control value derived from the concentration of IGFBP2 in blood samples from healthy patients.

FIELD OF THE INVENTION

The invention relates to a method for classifying a patient at risk forheart failure, wherein said method comprises the steps of (i) measuringthe concentration of IGFBP2 in a sample obtained from said patient and(ii) comparing the concentration of IGFBP2 measured in step (i) to acontrol value derived from the concentration of IGFBP2 in samples frompatients who are at particular stages of heart failure and/or to acontrol value derived from the concentration of IGFBP2 in blood samplesfrom healthy patients.

BACKGROUND OF THE INVENTION

Prevalence of heart failure (HF) is growing because of the ageing andthe cardiovascular risk factors in general population [Delahaye, F. etal., 2001]. The HF diagnosis remains too often complicated because ofatypical presentation and the need to specialized care access. To helpclinicians diagnose heart failure, blood HF biomarkers have beenproposed, such as the natriuretic peptides (NP). However, NP havelimitations which sustains a need for more specific and more acuratebiomarkers that would allow for facilitated large scale HF screenings.In addition, 30% of the patients admitted to emergency care for acutedyspnea have a brain natriuretic peptides (BNP) concentration in a<<gray zone>> that does not allow for diagnosis. In these cases, HFdiagnosis will require costly and time consuming examinations. However,it is recognized that a rapid diagnosis and early medical care of thepatient have a positive impact on the patient's health and also lowerthe cost of the treatment.

The article Hassfeld S. et al 2007 discloses the use of IGFBP2 as abiomarker for the prognostic of patients with dilated cardiomyopathy whorepresents an etiological subset of HF patients and doesn't disclose theuse of the IGFBP2 for the diagnostic of heart failure.

SUMMARY OF THE INVENTION

The inventors have launched a prospective monocentric case-control studyand investigated for urinary polypeptides specific to acute (AHF) orchronic heart failure (CHF) with holistic analytical strategy by usingthe capillary electrophoresis-mass spectroscopy technique (CE-MS). Theyfind that IGFBP2 concentration may be used as a biomarker of heartfailure as a biomarker to classify patients with heart failure.

Thus, the invention relates to a method for classifying a patient atrisk for heart failure, wherein said method comprises the steps of (i)measuring the concentration of IGFBP2 in a sample obtained from saidpatient and (ii) comparing the concentration of IGFBP2 measured in step(i) to a control value derived from the concentration of IGFBP2 insamples from patients who are at particular stages of heart failureand/or to a control value derived from the concentration of IGFBP2 inblood samples from healthy patients.

DETAILED DESCRIPTION OF THE INVENTION Classification and DiagnosticMethod

The invention relates to a method for classifying a patient at risk forheart failure, wherein said method comprises measuring the concentrationof IGFBP2 in a sample obtained from said patient.

In a particular embodiment, said method further comprises the steps of:

(i) measuring the concentration of IGFBP2 in a sample obtained from saidpatient,

(ii) comparing the concentration of IGFBP2 measured in step (i) to athreshold value derived from the concentration of IGFBP2 in samples frompatients who are at particular stages of heart failure and/or to athreshold value derived from the concentration of IGFBP2 in samples fromhealthy patients.

The invention also relates to a method for diagnosis of heart failure ina patient comprising the steps consisting of i) determining theconcentration of IGFBP2 in a sample obtained from said patient; and ii)comparing said concentration to a control value.

In a particular embodiment, the patient has significant comorbidconditions, including hypertension, coronary heart disease and diabetesfor example diabetes mellitus.

In another particular embodiment, the patient is on diuretics orantiplatelet agents.

In another particular embodiment, the patient is more than 50 years old.In another particular embodiment, the patient is more than 60 years old.

In one embodiment, the heart failure may be an asymptomatic heartfailure, a chronic heart failure or an acute heart failure.

Typically, the sample according to the invention may be a blood, plasma,serum, lymph, urine sample, cardiac tissues like atria or ventricle orliver. In a particular embodiment, said sample is plasma or urine.

As used herein, the term “IGFBP2” for “Insulin-like GrowthFactor-Binding Protein 2” denotes a protein which serves as a carrierprotein for Insulin-like growth factor 1 (IGF I) or Insulin-like growthfactor 2 (IGF II). As used herein, the term “IGFBP2” denotes alsofragments of IGFBP2. As used herein, the term “fragments of IGFBP2”denotes shorter peptides becoming from chemical or biochemicalhydrolysis of IGFBP2.

Thus, in a particular embodiment, the invention relates a method forclassifying a patient at risk for heart failure or to a method fordiagnosis of heart failure in a patient according to the patient bydetermining the concentration of fragments of IGFBP2.

As used herein, the term “heart failure” denotes inability of the heartto supply sufficient blood flow to meet the body's needs and thispathology is well-described in medicine practice. This term encompasseschronic heart failure, acute heart failure, myocardial infarction,unstable angina, diastolic dysfunction, systolic dysfunction anddiabetic cardiomyopathy.

As used herein, the term “chronic heart failure” denotes a long termsituation, usually with stable treated symptomatology.

As used herein, the term “acute heart failure” denotes to sudden onsetheart failure, as well as acute “exacerbated” or “decompensated” heartfailure, referring to episodes in which a patient with known chronicheart failure or devoid of chronic heart failure abruptly developsworsening symptoms and requires hospitalization. Common symptoms ofcomplications due to acute heart failure include, but are not limitedto, dyspnea due to pulmonary congestion or cardiogenic shock due to lowcardiac output, easy fatigueability (exercise intolerance), peripheraledema, anasarca (pronounced generalized edema), nocturia (frequentnighttime urination), bradycardia, heart block, hypotension, dizziness,syncope, diabetes, oliguria or anuria, hypokalemia, bronchospasm, coldsweat, and asthma.

A patient with a heart failure is classified according to aninternational gradation namely the New York Heart Association (NYHA)functional classification. Functional classification of heart failure isgenerally done by the New York Heart Association FunctionalClassification (Criteria Committee, New York Heart Association. Diseasesof the heart and blood vessels). Nomenclature and criteria fordiagnosis, 6th ed. Boston: Little, Brown and co, 1964; 114). Thisclassification stages the severity of heart failure into 4 classes(I-IV).

A patient with cardiac disease but resulting in no limitation ofphysical activity is classified as a NYHA class I. Ordinary physicalactivity does not cause undue fatigue, palpitation, dyspnea or anginalpain. A asymptomatic patient is classified as a NYHA class I.

A patient with cardiac disease resulting in slight limitation ofphysical activity is classified as a NYHA class II. Ordinary physicalactivity results in fatigue, palpitation, dyspnea or anginal pain. Theyare comfortable at rest.

A patient with cardiac disease resulting in marked limitation ofphysical activity is classified as a NYHA class III. Less than ordinaryactivity causes fatigue, palpitation, dyspnea or anginal pain. They arecomfortable at rest.

A patient with cardiac disease resulting in inability to carry on anyphysical activity without discomfort is classified as a NYHA class IV.Symptoms of cardiac insufficiency or of the anginal syndrome may bepresent even at rest. If any physical activity is undertaken, discomfortis increased.

According to the method for classifying a patient at risk for heartfailure, more a patient will have a high concentration of IGFBP2, morehis heart failure will be severe.

For example and according to thresholds value determined by theinventors, a patient with a high concentration of IGFBP2, for examplemore than 1300 ng/ml in plasma, will be classified as having an heartfailure of class IV.

The term “detecting” or “determining” as used above includes qualitativeand/or quantitative detection (measuring levels) with or withoutreference to a control. Typically IGFBP2 concentrations may be measuredfor example by capillary electrophoresis-mass spectroscopy technique(CE-MS) or ELISA performed on the sample.

Preferably, the invention relates to a method for diagnosis of heartfailure in a patient comprising a step a) consisting of measuring IGFBP2concentration in a sample obtained from said patient. Preferably, themethod of the invention further comprises a step of comparing theconcentration of IGFBP2 obtained in step a) to a threshold level.

The “control” may be a healthy subject, i.e. a subject who does notsuffer from any heart failure. The control may also be a subjectsuffering from heart failure. Preferably, said control is a healthysubject.

Detection of IGFBP2 concentration in the sample may also be performed bymeasuring the level of IGFBP2 protein. In the present application, the“level of IGFBP2 protein” means the quantity or concentration of saidIGFBP2 protein. In another embodiment, the “level of IGFBP2” means thelevel of IGFBP2 fragments.

Such methods comprise contacting a sample with a binding partner capableof selectively interacting with IGFBP2 protein peptides present in thesample. The binding partner is generally an antibody that may bepolyclonal or monoclonal, preferably monoclonal.

The presence of the protein can be detected using standardelectrophoretic and immunodiagnostic techniques, including immunoassayssuch as competition, direct reaction, or sandwich type assays. Suchassays include, but are not limited to, Western blots; agglutinationtests; enzyme-labeled and mediated immunoassays, such as ELISAs;biotin/avidin type assays; radioimmunoassays; immunoelectrophoresis;immunoprecipitation, capillary electrophoresis-mass spectroscopytechnique (CE-MS). etc. The reactions generally include revealing labelssuch as fluorescent, chemiluminescent, radioactive, enzymatic labels ordye molecules, or other methods for detecting the formation of a complexbetween the antigen and the antibody or antibodies reacted therewith.

The aforementioned assays generally involve separation of unboundprotein in a liquid phase from a solid phase support to whichantigen-antibody complexes are bound. Solid supports which can be usedin the practice of the invention include substrates such asnitrocellulose (e. g., in membrane or microtiter well form);polyvinylchloride (e. g., sheets or microtiter wells); polystyrene latex(e.g., beads or microtiter plates); polyvinylidine fluoride; diazotizedpaper; nylon membranes; activated beads, magnetically responsive beads,and the like.

More particularly, an ELISA method can be used, wherein the wells of amicrotiter plate are coated with a set of antibodies against theproteins to be tested. A sample containing or suspected of containingthe marker protein is then added to the coated wells. After a period ofincubation sufficient to allow the formation of antibody-antigencomplexes, the plate(s) can be washed to remove unbound moieties and adetectably labeled secondary binding molecule is added. The secondarybinding molecule is allowed to react with any captured sample markerprotein, the plate is washed and the presence of the secondary bindingmolecule is detected using methods well known in the art.

Methods of the invention may comprise a step consisting of comparingIGFBP2 protein and fragments concentration in circulating cells with acontrol value. As used herein, “concentration of IGFBP2” refers to anamount or a concentration of a transcription product, for instance theprotein IGFBP2. Typically, a level of a protein can be expressed asnanograms per microgram of tissue or nanograms per milliliter of aculture medium, for example. Alternatively, relative units can beemployed to describe a concentration. In a particular embodiment,“concentration of IGFBP2” may refer to fragments of IGBP2. Thus, in aparticular embodiment, fragments of IGFBP2 may also be measured.

In one embodiment, the invention relates to a method for classifying apatient at risk for heart failure, wherein said method comprisesmeasuring the concentration of IGFBP2 in a sample obtained from saidpatient. As already explained, more a patient will have a highconcentration of IGFBP2, more his heart failure will be severe.

The inventors have established threshold values which are able toclassifying patient with heart failure.

When the measure of IGFBP2 concentration is performed by Elisa method inplasma, a patient with a concentration of IGFBP2 with less than 600ng/ml, preferably less than 500 ng/ml, even preferably less than 400ng/ml most preferably less than 300 ng/ml is indicative of a heartfailure of stage I according to the NYHA heart failure classification.

When the measure of IGFBP2 concentration is performed Elisa method inplasma, a patient with a concentration of IGFBP2 comprised between about600 ng/ml and about 1100 ng/ml, preferably between about 800 ng/ml andabout 1050 ng/ml, preferably between about 900 ng/ml and about 1000ng/ml, most preferably between about 925 ng/ml and about 975 ng/ml isindicative of a heart failure of stage II according to the NYHA heartfailure classification.

When the measure of IGFBP2 concentration is performed Elisa method inplasma, a patient with a concentration of IGFBP2 comprised between about1100 ng/ml and about 1300 ng/ml, preferably between about 1150 ng/ml andabout 1250 ng/ml, most preferably between about 1175 ng/ml and about1225 ng/ml is indicative of a heart failure of stage III according tothe NYHA heart failure classification.

When the measure of IGFBP2 concentration is performed by Elisa method isperformed by capillary electrophoresis-mass spectroscopy technique(CE-MS) in plasma, a patient with a concentration of IGFBP2 more than1300 ng/ml, preferably more than 1350 ng/ml, even preferably more than1400 ng/ml, most preferably more than 1450 ng/ml is indicative of aheart failure of stage IV according to the NYHA heart failureclassification.

In another embodiment, the invention relates to a method for diagnosisheart failure in a patient comprising determining the concentration ofIGFBP2 in a sample obtained from said patient and comparing saidconcentration to a threshold value.

When the measure of IGFBP2 protein or is performed by Elisa method thelevel of IGFBP2 in a patient suffering of heart failure is increased byat least 50%, preferably by at least 70%, preferably by at least 100%;preferably by at least 150%, preferably by at least 200%, preferably byat least 250%, more preferably by at least 300%, even more at least 400%compared to a control reference. In other words, preferably, when IGFBP2protein is measured by Elisa method, the quantity of IGFBP2 protein in apatient suffering of heart failure is increased by at least 50%,preferably by at least 70%, preferably by at least 100%; preferably byat least 150%, preferably by at least 200%, preferably by at least 250%,more preferably by at least 300%, even more at least 400% compared to acontrol reference.

Concentration of IGFBP2 in plasma has been measured by Elisa technique.The inventors have established a threshold value for concentration ofIGFBP2 to easily diagnose heart failure. Preferably, this thresholdvalue is more than 150 ng/ml, preferably more than 200 ng/ml, even mostpreferable more than 250 ng/ml, most preferably said threshold value ismore than 300 ng/ml.

Concentration of IGFBP2 in urine has been measured by Elisa technique inurine. The inventors have established a threshold value forconcentration of IGFBP2 to easily diagnose heart failure. Preferably,this threshold value is more than 2.5 ng/ml, most preferably saidthreshold value is more than 3 ng/ml.

Typically, a “threshold value”, “threshold level” or “cut-off value” canbe determined experimentally, empirically, or theoretically. A thresholdvalue can also be arbitrarily selected based upon the existingexperimental and/or clinical conditions, as would be recognized by aperson of ordinary skilled in the art. Preferably, the person skilled inthe art may compare the concentration of IGFBP2 obtained according tothe method of the invention with a defined threshold value.

Preferably, said threshold value is the mean concentration of IGFBP2 ofa population of healthy individuals. As used herein, the term “healthyindividual” denotes a human which is known to be healthy, i.e. whichdoes not suffer from heart failure, has never been subjected to suchchronic heart failure, and does not need any medical care.

Preferably, said threshold value is the mean concentration of IGFBP2 ofa population of sick individuals. As used herein, the term “sickindividual” denotes a human which is known to be sick, i.e. whichsuffers from heart failure at any stage of heart failure as according tothe NYHA heart failure classification.

Typically, the skilled person in the art may determine the concentrationof IGFBP2 in a biological sample, preferably plasma or urine, of 100individuals known to be healthy or sick. The mean value of the obtainedconcentrations is then determined, according to well known statisticalanalysis, so as to obtain the mean concentration of IGFBP2. Said valueis then considered as being normal and thus constitute a thresholdvalue. By comparing the concentrations of IGFBP2 to this thresholdvalue, the physician is then able to diagnose heart failure orclassifying patients. Indeed, by comparing the concentrations of IGFBP2obtained in a biological sample, preferably plasma or urine, of a givensubject to a threshold value, one can easily determine whether saidsubject suffers from heart failure or not or can easily determine thestage of the heart failure according to the NYHA heart failureclassification.

Accordingly, the physician would be able to adapt and optimizeappropriate medical care of a subject in a critical and life-threateningcondition suffering from heart failure. The determination of saidprognosis is highly appropriate for follow-up care and clinical decisionmaking.

Therefore, the invention is drawn to a method for diagnosis of heartfailure in a patient or for classifying a patient at risk for heartfailure comprising the following steps:

-   -   a) determining the concentration of IGFBP2 in a sample obtained        from said patient;    -   b) determining the mean concentration of IGFBP2 in a biological        sample of a population of healthy or sick individuals,        preferably 100 healthy individuals; and    -   c) a step of comparing the concentration of IGFBP2 obtained        of a) to the mean concentration of IGFBP2 obtained in b).

In a further embodiment of the invention, methods of the inventioncomprise measuring the concentration of at least one further biomarker.

The term “biomarker”, as used herein, refers generally to a molecule,the expression of which in a sample from a patient can be detected bystandard methods in the art (as well as those disclosed herein), and ispredictive or denotes a condition of the subject from which it wasobtained.

For example, the other biomarker may be selected from the group of heartfailure biomarkers consisting of brain natriuretic peptide (BNP),amino-terminal pro-brain natriuretic peptide (NT-pro BNP),norepinephrine, troponin, heart-type fatty acid binding protein, myosinlight chain-1, matrix metalloproteinase, tissue inhibitor of matrixmetalloproteinase, C-reactive protein (CRP), TNFalpha, soluble tumornecrosis factor receptor 1 (sTNFR1), soluble TNFR2 receptor, solubleIL-2 receptor, CD40-CD154, CCAM-I, P-selectin, tissue factor and vonWillebrand factor, urocortin, myeloperoxidase, and uric acid.

In a preferred embodiment, the further biomarker of heart failure is BNPor NT-pro BNP.

Yet another object of the invention relates to a kit for performing amethod of the invention, said kit comprising means for measuring theconcentration of IGFBP2 in a sample obtained from a patient. The kit mayinclude an antibody, or a set of antibodies as above described. In aparticular embodiment, the antibody or set of antibodies are labelled asabove described. The kit may also contain other suitably packagedreagents and materials needed for the particular detection protocol,including solid-phase matrices, if applicable, and standards. The kitmay also contain one or more means for the detection of a furtherbiomarker. Typically the kit may also contain means for the detection ofone or more heart failure biomarker selected from the group consistingof brain natriuretic peptide (BNP), amino-terminal pro-brain natriureticpeptide (NT-pro BNP), norepinephrine, troponin, heart-type fatty acidbinding protein, myosin light chain-1, matrix metalloproteinase, tissueinhibitor of matrix metalloproteinase, C-reactive protein (CRP),TNFalpha, soluble tumor necrosis factor receptor 1 (sTNFR1), soluble T2receptor, soluble IL-2 receptor, CD40-CD154, CCAM-I, P-selectin, tissuefactor and von Willebrand factor, urocortin, myeloperoxidase, galectin-3and uric acid.

In a one embodiment, kit of the invention comprises means for measuringthe concentration of IGFBP2 and means for measuring the concentration ofBNP or NT-pro BNP.

A further object of the invention relates to the use of IGFBP2 as abiomarker for heart failure.

The invention will be further illustrated by the following figures andexamples. However, these examples and figures should not be interpretedin any way as limiting the scope of the present invention.

FIGURES

FIG. 1: ROC curve analysis of IGFBP2 levels from CHF and AHF patients(n=80) vs control subjects (n=50).

FIG. 2: Plasma concentration of IGFBP2 (ng/ml) in Control; Chronic Heartfailure (CHF), and Acute heart failure (AHF) patients. Multiplecomparison was performed with Anova and Bonferroni post hoc test (***p<0.001).

FIG. 3: Urine concentration of IGFBP2 (ng/ml). Control, n=21; ChronicHeart failure (CHF), n=19. Comparisons were performed using the Studentt test where * is for p<0.001.

FIG. 4: Plasma concentration of IGFBP2 according to the NYHAclassification of heart failure stage. Multiple comparison was performedwith Anova and Bonferroni post hoc test (* p<0.01).

FIG. 5: Scatter plot of IGFBP2 versus BNP concentration in plasma.Estimated regression line is plotted including its 95% Confidentinterval (dashed lines).

FIG. 6: Plasma concentration of IGFBP2 and the left ventricular ejectionfractions are correlated. IGFBP2 Plasma concentration was measured byELISA and left ventricular ejection fraction (LVEF) by transthoracicechocardiography.

FIG. 7: IGFBP2 and BNP levels in plasma from the discovery-test set.Biomarkers measurements were performed with plasma from control patientwith cardiovascular risk factors (CRF) or heart failure (HF) patients(acute and chronic, see FIG. 1). * Significant difference; p<0.05.

FIG. 8: IGFBP2 and BNP levels in plasma from the validation set.

(A) IGFBP2 and BNP levels were assessed in cardiovascular risk factorpatients (CRF), non cardiac dyspnea (NCD), chronic heart failure (CHF)and acute heart failure (AHF) patients. * Significant difference;p<0.05. Horizontal dashed line corresponds to optimal cut-point at 556ng/ml.

FIG. 9: IGFBP2 and BNP levels in plasma from NCD and AHF patients fromthe validation set.

ROC curve analysis for NCD (n=17) vs AHF (n=24) patients with a BNPcomprise between 100 and 600 pg/ml. AUCs were 0.838 (CI 95%:0.690-0.934) for IGFBP2 significantly different from AUC=0.5 p<0.0001and 0.653 (CI 95%: 0.895-0.969) not significantly different from AUC=0.5p=0.109 fot BNP. *Pairwise comparison of ROC curve were significantbetween BNP and IGFBP2 with p=0.034.

FIG. 10: Analysis of a rat model for ischemic heart failure.

(A) Echocardiography analysis. (B) qPCR analysis of IGFBP2 mRNA levelsin rats hearts and livers. N=5 per group. * p<0.05. Rats had surgery atday 14 and tissues for mRNA analysis were collected at day 70.

TABLE 1 The discovery test-set demographic and clinical characteristics.This set was constituted of 28 cardiovascular risk factors patients(CRF) as “controls” that were compared to 12 acute heart failure (AHF)and 9 chronic heart failure (CHF) patients as “cases”. CRF HF (n = 28)(n = 21) P Age, years 53 ± 12 70 ± 15 <0.001 Sex, Female, % (F/M) 36(10/18) 52 (11/10) 0.262 BMI 28.0 ± 4.6  25.2 ± 5.8  0.076Cardiovascular risk factors Hypertensive, % (n) 50 (14) 52 (11) 1.000Diabete T2, % (n) 14 (5) 38 (8) 0.190 Dyslipedemia, % (n) 79 (22) 62(13) 0.222 Obesity, % (n) 28 (8) 24 (5) 0.528 Smoking, % (n) 14 (1) 19(4) 0.150 Cardiovascular history Coronaropathy artery 0 (0) 43 (9)<0.001 disease, % (n) Hypertensive HCM, 0 (0) 14 (3) 0.072 % (n)Hereditary HCM, 0 (0) 5 (1) 0.428 % (n) Valvular heart 0 (0) 9 (2) 0.178disease, % (n) Dilated cardiomy- 0 (0) 20 (4) 0.028 opathy, % (n) Toxiccardiomy- 0 (0) 20 (4) 0.028 opathy, % (n) Medication ACE inhibitor, %(n) 4 (1) 38 (8) 0.003 ARAII, % (n) 14 (4) 20 (4) 0.710 Beta-blocker, %(n) 7 (2) 52 (11) <0.001 Diuretic, % (n) 4 (1) 90 (19) <0.001 Vitamin Kantagonist, 0 (0) 28 (6) 0.003 % (n) Antiplatelet agent, 10 (3) 67 (14)<0.001 % (n) Statine, % (n) 32 (9) 52 (11) 0.147 Admission labs BNP,pmol/ml 30 [21-57] 595 [333-1063] <0.001 Creatinine clairance, 102[87-122] 56 [45-60] <0.001 ml/min C reactive protein, 1.9 [1.4-2.3] 31.0[12.9-63.3] <0.001 mg/l Na⁺, mM 140 ± 1  135 ± 6  <0.001 ALT, U/ml 30[26-40] 40 [23-66] 0.281 Admission vitals Mean Blood Pressure, 101 ± 11 83 ± 20 <0.001 mmHg Heart rate, Bpm 70 [68-75] 85 [81-104] <0.001Echocardiography LVEF, % 70 ± 9  31 ± 12 <0.001 LVEF < 40%, % (n) 0 (0)81 (17) <0.001 LVEF: left ventricular ejection fraction.

TABLE 2 Differentially represented polypeptides determined by CE-MS.Areas under curve (AUC) are indicated for the 9 polypeptides that arebetter predictors for HF. unadj. Polypeptide wilcox-p-value Adj.Bonferroni Adj. BH AUC x64054 6.40e−09 1.39e−05 1.39e−05 0.988 x530786.05e−08 1.32e−04 4.39e−05 0.947 x102021 1.19e−07 2.58e−04 5.17e−050.945 x69979 2.62e−07 5.69e−04 6.44e−05 0.934 x52446 3.35e−07 7.28e−046.44e−05 0.929 x13188 1.54e−08 3.35e−05 1.67e−05 0.929 x3806 4.15e−079.02e−04 6.44e−05 0.925 x140665 3.62e−07 7.86e−04 6.44e−05 0.925 x914631.15e−07 2.49e−04 5.17e−05 0.923 “p” values unadjusted and afterBonferroni or Benjamini Hochberg (BH) adjustment.

TABLE 3 Validation set demographic and clinical characteristics,cardiovascular risk factors (CRF); non cardiac dyspnea (NCD), chronicheart failure (CHF) and acute heart failure (AHF) patients wererecruited. CRF NCD CHF AHF (n = 39) (n = 43) P (n = 58) P (n = 39) PAge, years 57 ± 11 66 ± 16 0.022 62 ± 13 0.022 73 ± 15 <0.001 Sex,Female, % 41 (16/23) 54 (23/20) 0.364 32 (19/40) 0.498 54 (21/18) 0.364(F/M) BMI 26.8 ± 4.3  25.0 ± 6.0  0.181 25.6 ± 4.2  0.173 27.4 ± 4.3 0.688 Cardiovascular risk factors Hypertensive, % 31 (12) 49 (21) 0.15038 (22) 0.612 81 (31) <0.001 (n) Diabete T2, % (n) 15 (6) 21 (9) 0.71730 (17) 0.181 24 (9) 0.567 Dyslipedemia, % 80 (32) 33 (14) <0.001 59(34) 0.027 55 (21) 0.015 (n) Obesity, % (n) 31 (12) 14 (6) 0.116 14 (8)0.077 20 (8) 0.437 Smoking, % (n) 10 (4) 30 (13) 0.050 14 (8) 0.838 10(4) 0.709 Cardiovascular history Coronaropathy 5 (2) 14 (6) 0.331 51(30) <0.001 52 (20) <0.001 artery disease, % (n) Hypertensive HCM, 0 (0)9 (4) 0.150 8 (5) 0.157 13 (5) 0.044 % (n) Hereditary HCM, % 0 (0) 0 (0)0.740 8 (5) 0.157 0 (0) 0.740 (n) Valvular heart 0 (0) 9 (4) 0.150 20(12) 0.007 16 (6) 0.033 disease, % (n) Dilated 0 (0) 0 (0) 0.740 24 (14)<0.001 8 (3) 0.239 cardiomyopathy, % (n) Toxic 0 (0) 0 (0) 0.740 8 (5)0.157 8 (3) 0.239 cardiomyopathy, % (n) Medication ACE inhibitor, % (n)10 (4) 21 (9) 0.308 64 (37) <0.001 37 (14) 0.016 ARAII, % (n) 13 (5) 19(8) 0.679 10 (6) 0.960 21 (8) 0.543 Beta-blocker, % (n) 18 (7) 23 (10)0.749 73 (42) <0.001 55 (21) 0.002 Diuretic, % (n) 10 (4) 56 (24) <0.00174 (43) <0.001 89 (35) <0.001 Vitamin K 0 (0) 30 (13) <0.001 46 (27)<0.001 29 (11) 0.001 antagonist, % (n) Antiplatelet agent, 10 (4) 23(10) 0.205 55 (32) <0.001 60 (23) <0.001 % (n) Statine, % (n) 38 (15) 21(9) 0.134 60 (35) 0.056 37 (14) 1.000 Admission labs BNP, pmol/ml 25[21-48] 95 [61-169] <0.001 423 [303-636] <0.001 686 [370-1207] <0.001Creatinine 86 [83-96] 73 [58-87] 0.013 58 [51-72] <0.001 42 [31-53]<0.001 clairance, ml/min C reactive protein, 1.9 [1.2-2.7] (39) 9.6[4.6-23.5] <0.001 8.6 [6.3-13.0] <0.001 26.0 [19.7-47.3] <0.001 mg/lNa⁺, mM 140 ± 2  138 ± 4.3  0.005 138 ± 3  <0.001 137 ± 6  <0.001 ALT,U/ml 31 [26-38] 23 [19-28] 0.006 30 [25-38] 0.982 38 [24-51] 0.471Admission vitals Mean Blood 98 ± 11 94 ± 14 0.120 85 ± 12 <0.001 89 ± 240.037 Pressure, mmHg Heart rate, Bpm 65 [60-67] 88 [81-95] 0.006 76[70-84] <0.001 91 [84-99] <0.001 Echocardiography LVEF, % 70 ± 10 64 ±12 0.010 36 ± 13 <0.001 42 ± 19 <0.001 LVEF < 40%, % (n) 0 (0) 0 (0)0.740 60 (35) <0.001 50 (23) <0.001 LVEF: left ventricular ejectionfraction.

TABLE 4 Correlations of IGFBP2 and BNP levels with clinicalcharacteristics. Rho: Spearman rank correlation coefficient, n = 228.Rho > 0.5 moderate to high relationship are in bold. IGFBP2 BNP rho P nrho P n Age, years (n) 0.397 <0.0001 179 0.331 <0.0001 177 Sex, Female,% 0.006 0.9358 180 0.053 0.4832 178 (F/M) BMI (n) −0.288 0.0002 166−0.209 0.0071 165 Cardiovascular risk factors Hypertensive, % (n) 0.1300.0839 179 0.081 0.2834 178 Diabete, % (n) 0.180 0.0161 179 0.090 0.2335178 Dyslipedemia, % (n) −0.228 0.0021 179 −0.250 0.0007 178 Obesity, %(n) −0.243 0.0010 180 −0.158 0.0357 178 Smoking, % (n) 0.011 0.8834 1800.047 0.5370 178 Cardiovascular history Coronaropathy 0.381 <0.0001 1790.371 <0.0001 178 artery disease, % (n) Hypertensive HCM, 0.156 0.0368179 0.067 0.3740 178 % (n) Hereditary HCM, % 0.141 0.0595 179 0.2040.0063 178 (n) Valvular heart 0.302 <0.0001 179 0.281 0.0001 178disease, % (n) Dilated 0.182 0.0147 179 0.211 0.0046 178 cardiomyopathy,% (n) Toxic 0.205 0.0060 179 0.184 0.0140 178 cardiomyopathy, % (n)Medication ACE inhibitor, % 0.256 0.0005 179 0.245 0.0010 178 (n) ARAII,% (n) −0.044 0.5616 179 −0.022 0.7736 178 Beta-blocker, % 0.325 <0.0001179 0.364 <0.0001 178 (n) Diuretic, % (n) 0.704 <0.0001 179 0.674<0.0001 178 Vitamin K 0.268 0.0003 179 0.311 <0.0001 178 antagonist, %(n) Antiplatelet agent, 0.380 <0.0001 179 0.311 <0.0001 178 % (n)Statine, % (n) 0.074 0.3232 179 0.061 0.4155 178 Admission labs BNP,pmol/ml (n) 0.773 <0.0001 178 — — — Creatinine clairance, −0.681 <0.0001178 −0.587 <0.0001 177 μmol/l (n) C reactive protein, 0.615 <0.0001 1790.614 <0.0001 177 mg/l (n) Na⁺, mM (N) −0.331 <0.0001 179 −0.409 <0.0001178 ALT, U/ml (N) 0.075 0.3245 174 0.115 0.1316 173 Mean Blood Pressure,mmHg (n) Heart rate, Bpm (n) −0.419 <0.0001 169 −0.397 <0.0001 168Echocardiography 0.410 <0.0001 172 0.452 <0.0001 171 LVEF, % (n) −0.653<0.0001 178 −0.669 <0.0001 176

TABLE 5 External validation cohort demographic and clinicalcharacteristics. COPD AHF (n = 10) (n = 30) P Age, years 57 ± 10 73 ± 10<0.001 Gender, Female, 30 (3/7) 23 (7/23) 0.689 % (F/M) Cardiovascularrisk factors Hypertensive, % (n) 30 (3) 63 (19) 0.140 Diabete T2, % (n)40 (4) 43 (13) 1.000 Dyslipedemia, % (n) 30 (3) 47 (14) 0.470 Obesity, %(n) 10 (1) 6 (2) 1.000 Cardiovascular history Coronaropathy artery 10(1) 43 (13) 0.069 disease, % (n) Valvular heart 0 (0) 30 (9) 0.080disease, % (n) Clinical presentation Acute heart failure — 30 (9) —Acutely decompensated — 60 (18) — heart failure, % (n) Pulmonary edema,% (n) — 10 (3) — Medication ACE inhibitor or 30 (3) 63 (19) 0.140 ARAII,% (n) Beta-blocker, % (n) 0 (0) 57 (17) 0.010 Diuretic, % (n) 40 (4) 80(24) 0.041 Vitamin K antagonist, 10 (1) 47 (14) 0.059 % (n) Antiplateletagent, % (n) 30 (3) 60 (18) 0.148 Statine, % (n) 20 (2) 57 (17) 0.691Admission labs BNP, pmol/ml 14 [10-19] 1782 [1340-2773] <0.001Creatinine, μmol/l 80 [65-100] 120 [98-142] 0.015 C reactive protein,mg/l 4.0 [0.0-14.5] 10 [0.7-19.5] 0.209 Na⁺, mM 139 ± 3  136 ± 7  <0.043Admission vitals Mean Blood Pressure, 98 ± 13 93 ± 17 0.443 mmHg Heartrate, Bpm 104 ± 28  88 ± 26 0.107 Echocardiography LVEF, % — 35 [20-60]— LVEF: left ventricular ejection fraction.

EXAMPLES Example 1 First Patient's Analysis

Material & Methods

Patients:

1. Population:

We performed a monocentric transversal study with the inclusion of over200 patients between November 2010 and March 2011 from the ToulouseRangueil University Hospital. Three groups of patients were constituted:Chronic heart failure, (CHF), Acute heart failure (AHF) and control. Allpatients have signed a consent agreement and the biosample collectionwas approved by the French ministry of health, CCTIR, CNIL and ethiccommittee (CPP). Patients under 18 years old or not able to understandor to sign the agreement were excluded as well as kidney failure ortransplanted patients.

a. Chronic Heart Failure Patients (CHF):

We included patients with a known stable CHF (>3 months without anydecompensation) ranging from NYHA stage I to IV with miscellaneousetiologies (ischemic cardiopathy (CMI), valvular (CMV),post-hypertensive (CMH post-HTA), hypertrophic genetic cardiomyopathy(CMH gene), primary dilated cardiomyopathy or toxic (CMD)), Rightventricle arythmogenic dysplasia arythmogen and congenitalcardiomyopathy. Inclusion required a clear diagnosis of heart failure(clinical, history of the disease, transthoracic echocardiography (TTE)and/or BNP). These patients were admitted in several cardiology services(hospitalization, consultation form Pr Galinier and Pr Carrie units)after their admission for heart failure.

b. Acute Heart Failure (AHF):

We included patients admitted for acute cardiac decompensation whateverthe type was (left, right, mixed, low output, cardiogenic choc) to beable to identify putative CHF and AHF biomarkers.

c. Control:

Control patients were included through the artherosclerosis preventiondepartment of Rangueil University Hospital during day hospitalization.

2. Clinical Data:

For all patients, anthropometric data (weight, height, gender) clinicalhistory, electrocardiographic and biological data (plasmatic sodium,creatinine, hepatic status, prothrombine, CRP, hematocrite andhemoglobin) were collected. BNP levels data were collected for CHF andAHF patients. All these examinations were requested during the treatmentof the by the physician in charge of the patients and were performed tomonitor the heart failure stage but also the kidney and liver function,hydratation and inflammatory level. All medications were recorded.

3. Echocardiography:

Transthoracic echocardiography (TTE) was performed for all subjectsincluded by a single cardiologist on a dedicated machine (Kontron)allowing for data collection during procedure and post-processing of thedata using the software My Lab Desk—Kontron for each patient.

TTE allowed for systematic volumes and diameters measurements, leftventricle systolic and diastolic function. In addition, right ventriclefunction was analyzed as well as aortic, mitral or tricuspidvalvulopathies. TTE was considered as <<gold standard>> for heartfailure diagnosis that was completed with its etiology according to theEuropean and American current recommendations.

Biological Samples:

Urine were collected in standard polypropylene tubes and immediatelyfrozen and maintained at −80° C. Plasma were collected on EDTA tubes,centrifuged, aliquoted on ice and immediately frozen at −80° C.

Analytical Methods:

CE-MS was performed using standard procedure [Mischak, H. et al., 2010].Briefly, peptides were electrophoretically separated on 90 cm long and50 μm diameter silice capilar (Beckmann-Coulter, Fullerton, Calif., USA)coupled to a ESI-TOF mass spectrometer (electrospray ionisation—time offlight) (MicroTOF, Brucker-Daltonic, Bremen, Germany). CE-MS buffer was20% (v/v) acetonitrile and 250 mM formic acid in HPLC water.Electrophoretic separation is performed during 60 min under an electricfield (+35 to −40 kV) leading to a 13 μA intensity. Capillarytemperature is maintained to +35° C. during runs.

Enzyme-linked immunosorbent assay (ELISA) IGFBP2 quantization wasperformed using R&D SYSTEMS EUROPE LTD reagents according to themanufacturer ELISA reagent protocol.

Results

We first screened the urinary proteome of 50 patients (9 CHF, 13 AHF, 28healthy controls apparied for age sex and risk factor), which led toreveal a panel of polypeptides specific to HF. One polypeptide (x64054,mass 1878,792 Da; Capillary electrophoresis time t=20.72 min) seemedvery relevant because it could discriminate AHF and CHF with a highspecificity and sensibility based on CE-MS data (AUC=0.99; p<0.0001).Using MALDI-TOF analysis, we identified this putative biomarker as afragment of the Insulin-like growth factor-binding protein 2 (IGFBP2).

The validation of IGFBP2 as a putative biomarker was performed by ELISAusing both plasma and urine concentration measurements in 200 patients.ROC curve analysis provided an AUC value of 0.988, p<0.0001 (FIG. 1).Clearly plasma (FIG. 2) and urinary (FIG. 3) concentration of IGFBP2 arestrongly enhanced in CHF and AHF patients. Moreover the elevation ofIGFBP2 concentration in plasma was dependant on the severity of heartfailure as indicated by the NYHA classification (FIG. 4). Furthermore,we noticed that IGFBP2 and BNP levels were weakly correlated giving moreimportance to this new biomarker as an almost independent indicator(FIG. 5). Finally, we observed that the IGFBP2 plasma level and the leftventricular ejection fraction were negatively correlated, indicating aphysiological link between bloodstream IGFBP2 level and the heartfunction and bringing IGFBP2 levels as possible estimate of the heartpump status (FIG. 6). Therefore, we propose that elevated IGFBP2concentration could be used as a biomarker of heart failure.

Example 2 Second Patient's Analysis

Material & Methods

Patient Inclusions

Two independent cohorts were used in this study. A discovery-validationcohort with 228 patients who were recruited between November 2010 andNovember 2011 at the Rangueil University Hospital (Toulouse, France) andan external validation cohort with 40 patients who were recruitedbetween 2009 and 2011 at the Lariboisière University Hospital (Paris,France).

To focus on specific biomarkers of heart failure without prejudice toetiology or severity of the heart failure, the case group of thediscovery-validation cohort was constituted of patients suffering fromchronic (CHF) or acute (AHF) heart failure. CHF patients had a knownstable HF with >3 months without any decompensation episodes, whateverthe stage of clinical severity (stage I to IV of NYHA classification)and, regardless of etiology. Diagnosis of heart failure had beenformally established from clinical observations, heart diseasefollow-up, transthoracic echocardiography (TTE) and BNP monitoring.These patients were included during their regular scheduled visit at thehospital. AHF patients were recruited whatever the clinical presentation(left, right, mixed, low flow-cardiogenic shock.

The control group of the discovery-validation cohort was constituted ofpatients without HF but with cardiovascular risk factors (CRF) or CRFand non cardiac dyspnea (NCD) for the discovery step and the validationstep, respectively. CRF patients were recruited during their scheduledvisit at the atherosclerosis prevention center of the RangueilUniversity Hospital. Inclusion in this group required the exclusion ofall patients with a history, clinical signs, biological, orechocardiographic evidence of heart failure (systolic or diastolicdysfunction).

External validation cohort was constituted at the LariboisièreUniversity Hospital (Paris, France) with COPD patients (with BNP<20pg/ml to test “pure” COPD without any right or left cardiac stress) ascontrol patient and AHF patients as cases patients.

For all subjects anthropometric data (weight, height, gender), clinicalhistory, biological data and electrocardiographic were collected (Tables1, 3, 5). All these examinations were performed during the treatment bythe physician in charge of the patients and were performed to monitorthe heart failure stage but also the kidney and liver function,hydratation and inflammatory level. All medications were recorded.

TTE was performed for all subjects included by a single cardiologist.Echocardiography (Konton Imagic, Kontron, Saint German en Laye, France)allowed for systematic volumes and diameter measurements, left ventriclesystolic and diastolic function and ejection fraction measurements.Patients with renal dialysis or transplant (stage 5D and 5T) wereexcluded.

The research protocol was registered in a clinical database(ClinicalTrials.gov NCT01024049) conforms to the ethical guidelines ofthe 1975 Declaration of Helsinki. The protocol was approved by theinstitution's human research (COSSEC) and regional ethics committee(Comité de Protection des Personnes (CPP) # DC 2008-452). Writteninformed consent was obtained from all participants and/or their legallyauthorized representatives.

Discovery and Validation Sets

We first randomly constituted a discovery-test set of 49 subjects out ofthe 228 patients from discovery-validation cohort. Twenty-one HFpatients with 9 out of the 67 AHF and 12 out of the 51 AHF constitutedthe cases subset and 28 out the 67 CRF patients constituted the controlssubset. Urines from these 49 subjects were used for CE-MS proteomicanalysis (Table 1). X64054 peptide isolated through this analysis wasfurther identified below as IGFBP2 and tested in plasma of thediscovery-test set. Furthermore two validation cohorts were constituted.The first comprising patients from Toulouse university hospital (Table3); The validation set included 179 patients with a control subsetconstituted of 39 CRF and 43 NCD and a case subset constituted of 39 AHFand 58 CHF.

A second validation cohort was constituted with 40 patients from ParisLariboisière University Hospital. This external validation cohortincluded 10 COPD and 30 AHF patients (Table 5).

Biological Samples

All subjects were venesected and peripheral venous blood was drawn intosodium/EDTA tubes. After centrifugation at 1500 g at 4° C. for 10 min,plasma was separated, aliquoted and stored at −80° C. until assayed.Subjects also provided a morning urine sample, and 20 ml was collectedinto polypropylene collection pot, aliquoted and stored as above.

Analytical Methods

Sample Preparation and Capillary Electrophoresis Coupled to MassSpectrometry (CE-MS) Analysis

All participants collected morning urine samples the day of theechocardiographic examinations.

Aliquots were stored at −80° C. until the time of processing. Urinesamples were then processed as previously described 13 and thenresuspended in HPLC-grade water shortly before CE-MS analyses. CE-MSanalysis was performed as described using a P/ACE MDQ capillaryelectrophoresis system (Beckman Coulter, Villepinte, France) on-linecoupled to a MicroQTOF MS (Bruker Daltonics, Bremen, Germany). The ESIsprayer (Agilent Technologies, Palo Alto, Calif., USA) was grounded, andthe ion spray interface potential was set between −4.0 and −4.5 kV. Dataacquisition and MS acquisition methods were automatically controlled bythe CE via contact-close-relays. Spectra were accumulated every 3 s,over a range of m/z 350 to 3000. Details on accuracy, precision,selectivity, sensitivity, reproducibility, and stability of the CE-MSmethod have been provided previously.

Data Processing

Mass spectra were processed using MosaiquesVisu software (Mosaiques,Hannover, Germany), including peak picking, deconvolution, andde-isotoping. Migration time and peak intensity were normalized usinginternal polypeptide standards. These fragments are believed to be theresult of normal biological processes and appear to be unaffected by anydisease state studied to date on the basis of 20,000 samples in ourdatabase. The resulting peak list characterizes each polypeptide by itsmolecular mass, normalized capillary electrophoresis migration time, andnormalized signal intensity. All detected polypeptides were deposited,matched, and annotated in a Microsoft SQL database, allowing furtheranalysis and comparison of multiple patient groups.

Statistical Methods and Identification of Biomarkers

We compared means and proportions of clinical and echocardiographiccharacteristics of the discovery and test samples by means of a t-testand the x2 statistics, respectively, using SAS software, version 9.1.3(SAS Institute, Cary, N.C., USA). In the discovery phase, we comparedthe natural logarithm-transformed signal amplitude of the CE-MS urinarypolypeptide profile between patients and controls using the Wilcoxonrank sum test. This non-parametric test is suitable for skewed proteomicdata. We tested the null hypothesis that patients and controls have thesame continuous distribution of signal amplitude of the CE-MS urinarypolypeptide profile. The signal amplitude represents the calibratedcounts (intensity) recorded by the mass spectrometry device. Statisticaladjustment for multiple testing was performed by applyingBenjamini-Hochberg correction. We searched for a cluster of urinarypolypeptides discriminating between cases and controls based on thedistribution of biomarkers in individual subjects. For each case andeach control, the selected polypeptides were combined into a singlesummary variable, using the support-vector machine-based MosaClustersoftware, version 1.6.5. In the test set, researchers blinded to theclinical condition of the study participants measured the clusterpolypeptides. After breaking the code, we calculated the sensitivity andthe specificity based on tabulating the number of correctly classifiedsamples in the test set, using receiver operating characteristic (ROC)plots. The area under the ROC curve (AUC) provides a single measure ofoverall accuracy that is independent of any particular threshold.

Sequencing

The urine samples were analysed on a Dionex Ultimate 3000 RSLS nano flowsystem (Dionex, Camberly UK), essentially as described (Carty et al.,2011; Metzger et al., 2012). The samples (5 μl) were loaded onto aDionex 100 μm×2 cm 5 μm C18 nano trap column at a flowrate of 5 μl/minby a Ultimate 3000 RS autosampler (Dionex, Camberley UK) The compositionof the loading solution was 0.1% formic acid and acetonitrile (98:2).Once loaded onto the trap column the sample was then washed off into anAcclaim PepMap C18 nano column 75 μm×15 cm, 2 μm 100 Å at a flowrate of0.3 μm/min. Elution was performed with a linear gradient of solvent A,0.1% formic acid and acetonitrile (98:2) against solvent B, 0.1% formicacid and acetonitrile (20:80) starting at 1% B for 5 minutes rising to30% at 90 minutes then to 50% B at 120 minutes. The trap and nano flowcolumn were maintained at 35° C. in a column oven in the Ultimate 3000RSLC. The eluent from the column was directed to a Proxeon nano sprayESI source (Thermo Fisher Hemel UK) operating in positive ion mode theninto an Orbitrap Velos FTMS. The ionisation voltage was 2.5 kV and thecapillary temperature was 200° C. The mass spectrometer was operated inMS/MS mode scanning from 380 to 2000 amu. The fragmentation method wasHCD at 35% collision energy. The ions were selected for MS2 using a datadependant method with a repeat count of 1 and repeat and exclusion timeof 15 s. Precursor ions with a charge state of 1 were rejected. Theresolution of ions in MS1 was 60,000 and 7,500 for HCD MS2. Data filesfrom experiments performed on the HCD-enabled LTQ were searched againstthe IPI human non-redundant database using Thermo Proteome Discoverer,without any enzyme specificity. No fixed modification was selected, andoxidation of methionine and proline were set as variable modifications.Mass error window of 10 ppm and 0.05 Da were allowed for MS and MS/MS,respectively. For further validation of obtained peptideidentifications, the strict correlation between peptide charge at theworking pH of 2 and CE-migration time was utilized to minimizefalse-positive identification rates 17. Calculated CE-migration time ofthe sequence candidate based on its peptide sequence (number of basicamino acids) was compared to the experimental migration time.CE-migration time deviations below ±2 min corresponding to the CE-MSmeasurement were accepted.

Immune Methods

Western blot were performed as already published 18 using rabbitmonoclonal anti-human IGFBP2 antibody, clone EPR3380(2) (Clinisciences,Nanterre, France). IGFBP2 enzyme-linked immunosorbent assay (R&DSystems, Inc., Minneapolis, Minn., USA) was used to measure human IGFBP2as per the manufacturer's specifications.

mRNA Extractions, Reverse Transcription (RT) and Realtime QuantitativePCR (qPCR)

mRNA extractions and RT-qPCR was performed as already described usingthe different primers as already performed [Harmancey R et al, 2007].

Statistical Analysis

Because of the very large amount of signals in comparison to the numberof patients tested in CE-MS analysis, only signal with a signal to noiseratio over 4 times the background were kept. Unless otherwise specified,continuous variables are presented as means (±SD) categorical variablesas percentages. For continuous variables, a Student's t-test orMann-Whitney rank sum test when normality test failed or for categoricalvariables a chi square test was used to determine their statisticaldifferences between groups. Statistical analyses were performed using Rcomputation language (http://www.R-project.org) and Medcalc (Medcalc,version 11.6.0.0, Medcalc software bva, Belgium).

Results

Discovery Study

Demographic and clinical data of the discovery-test set are presented inTable 1. Significant differences between control and HF patients formedication, admission labs, echocardiography and admission vitalsparameters are in agreement with their clinical status Thus, plasma BNPand CRP concentrations were significantly higher in HF patients whereascreatinine clearance, sodium concentration were reduced. Moreover, meanblood pressure and ejection fraction (EF) were reduced in HF patients.HF patients also had an increased heart rate. HF patients and were olderthan the control subjects (70±15 vs 53±12; p<0.001). 43% of the HFpatients had a history of CAD. Cardiovascular risk factors weresimilarly represented in the two groups.

Differentially Represented Polypeptides Determined by CE-MS andIdentification of a New Putative HF Biomarker.

We aimed at detecting putative biomarkers profiles that could be asignature HF using CE-MS analysis of urine samples as a first step.Based on the urine proteome analysis of the AHF and CHF patients (allstages and etiologies) and CRF control subjects, we have defined apolypeptide set specific to HF (9 polypeptides with AUC≧0.923, p<0.001(Benjamini Hochberg multiple testing correction) (Table 2). Onepolypeptide (x64054, mass 1878.792 Da; electrophoresis time t=20.7224 s)seemed very interesting because it showed an excellent discriminatingpower for HF with and AUC of 0.988, p=1.39.10-5. Therefore, we focusedon this peptide and could successfully identify it as the insulin likegrowth factor binding protein 2 (IPI:IPI00297284.1). We first checkedthe presence of IGFBP2 in human urine and blood and observed that IGFBP2was more abundant in plasma that in urine (data not shown). ELISAanalysis of IGFBP2 urinary concentration revealed that the concentrationwas 505±198 (n=35) fold lower than in plasma (not shown). Because ofthis observation, we further analyzed IGFBP2 in plasma samples by ELISA.

IGFBP2 Plasma Concentration

Analysis of IGFBP2 in plasma showed a significant increase in heartfailure patients vs control individuals with 1350±635 (p<0.001) and214±136 ng/ml, respectively (FIG. 7). BNP levels in these patientsdisplayed with a higher concentration in HF than in control patients;806±693 and 39±28 (p<0.001), respectively (FIG. 7).

Validation Study

Demographic and clinical data of patients included in the validation setare presented in Table 3. CRF patients have cardiovascular risk factorswithout any symptoms or objective parameters of HF. AHF patients werethe oldest group. AHF Patients had significant comorbid conditions,including hypertension (81%) coronary heart disease (52%) and diabetesmellitus (24%). Most patients were on diuretics (89%) and antiplateletagents (60%). Age distribution of patients of the CHF group is nestledin the control group between CRF and NCD groups. The CHF patients were62±13 years old with 68% male and the LVEF was ≦45% in 42 patients.Patients had significant comorbid conditions, including hypertension(37%) coronary heart disease (51%) and diabetes mellitus (30%). Again,most patients were on diuretics (78%) and antiplatelet agents (54%).There is no significant difference for gender between the groups. IGFBP2concentrations were significantly increased in CHF and AHF vs CRF or NCDpatients. This increase of IGFBP2 levels followed the similar pattern asBNP levels in this set of patients (FIG. 8). ROC curve analysis of CRFand NCD patients vs CHF and AHF patients showed an area under curve(AUC) of 0.933 for IGFBP2 with 0.81 Youden index associated withIGBP2 >556 ng/ml which was higher than BNP (0.870; p=0.038). Logisticregression of IGFBP2+BNP raised the AUC to 0.942 but did notsignificantly increased the performance of IGFBP2 (data not shown).

IGFFBP2 was further tested for cardiac diagnostic of acute dyspneapatients. Values of IGFBP2 and BNP concentrations from these acutedyspnea patients are presented to displays the global distribution ofthe patients (data not shown). The ROC curve analysis of NCD vs AHFpatients displayed an increased AUC for IGFBP2+BNP vs BNP (0.925 vs0.859; p=0.04). In these groups of patients, IGFBP2 discriminationperformance was not significantly different from the one of BNP (datanot shown). A clear difference between BNP and IGFBP2 diagnosticperformance was seen when the plasma BNP level was its poor diagnosiszone, which was extended here from 100 to 600 pg/ml which correspondedfor its lower level to the rule-out concentration and 600 pg/ml whichwas defined as a reasonable higher cut-off value to rule-in HF. Incontrast to BNP, which had no diagnostic value (AUC=0.643; 95% CI:0.479-0.787) in this zone of concentrations, IGFBP2 reached an AUC of0.838 (95% CI: 0.690-0.934) (FIG. 9).

IGFBP2 Levels and Correlations with Clinical Parameters

Univariate analysis of correlation between IGFBP2 and BNP with maincharacteristics parameter of the patients are reported in Table 4.IGFBP2 and BNP levels were strongly correlated together (rho=0.722;p<0.001). Furthermore BNP and IGFBP2 levels were similarly correlated todiuretic and C reactive protein, creatinine clearance and LVEF.

External Validation of IGFBP2 as a AHF Biomarker

We tested the predicting value of IGFBP2 for AHF diagnosis on a cohortof patients recruited at Paris Lariboisière Hospital. This cohortcomprised AHF and COPD patients and is described in Table 5. Use of thethreshold 556 ng/ml which was previously and independently determined inthe discovery-validation cohort as indicated above led to a sensitivityof 80% for AHF diagnostic and a specificity of 90% for COPD patients(data not shown).

Example 3 Animal Analysis

Material & Methods

Rats HF Model and Transthoracic Echocardiography

The investigation conformed to the National Institutes of Health Guidefor Care and Use of Laboratory Animals was allowed by the Inserm AnimalEthics Committee. The study, using myocardial infarction in 2 month oldSprague-Dawley rats (Janvier labs) by coronary artery ligation, wasapproved by the Local Animal Ethics Committee (# MP/03/03/01/12).Transthoracic echocardiographic analyses were performed for leftventricular ejection fraction measurement using the Vivid 7 pro 7echocardiographic system (GE Medical System) as already performed.

Results

Test of IGFBP2 in a Rat Model of Ischemic HF

At day 20, i.e 4 days after surgery induced ischemia, the animals had alowered ejection fraction (FIG. 10A) until day 70 when animals wereeuthanatized and the organs collected. Analysis of the gene expressionlevels in tissues showed that IGFBP2 mRNA levels were increased in theischemic animals atria compared with sham-operated (FIG. 10B).Interestingly and at this time point, atria IGFBP2 mRNA levels from HFanimals were ten times higher vs ventricle and 4 times increased vsliver.

Discussion

Plasma BNP or NT-proBNP levels are valuable tools to diagnose patientswith HF 2. Therefore, we compared both IGFBP2 diagnostic value to theone of BNP and the putative added value of IGFBP2 to BNP. The diagnosticperformance of IGFBP2 measurement led us to discriminate HF cases fromcontrol cases without heart disease (CRF and NCD patients) with anincreased AUC compared to the one of BNP. Logistic combination of IGFBP2and BNP led to an increased AUC compared to BNP alone when testing theuse of IGFBP2 and BNP in the discrimination between NCD and AHFpatients. The added value of IGFBP2 diagnostic performance was even moreevident in patients with moderate BNP elevation i.e. in the 100-600pg/ml concentration range.

IGFBP2 up-regulation point out a potential role for Insulin-like growthfactor (IGF)-binding proteins (IGFBPs) in HF and more largely involvesthe somatotrope axis that encompass hypothalamic hormones such ashypothalamic Growth-hormone-releasing-hormone (GHRH), hypohyseGrowth-hormone and IGF 1 and 2. IGFBPs confer regulation to IGFbioactivity but can also have a direct role. Clearly, IGF1'savailability is regulated by Insulin Growth Factor Binding ProteinIGFBPs. Only one to 5% of IGF1 is free in the blood stream, theremaining IGF1 is tightly bound to IGFBPs with an affinity that isgreater or equal to the one for its receptor. Thus, IGFBPs modulate IGF1and IGF1 receptor interaction. However, some IGFBPs were recently foundto have their own activity even in the absence of IGF, through a directinteraction with transcription factors and modulation of geneexpression.

IGFBP2 is the second most abundant IGFBP in human plasma. IGFBP2 ismostly an IGF1 inhibitor. Our correlation data confirmed that BNP andIGFBP2 plasma levels are not dependant on sex but are positivelyincreased with age and negatively with the body mass index.

IGF1 was recognized to be involved in growth and myocardial development28. IGF1 and it receptor are expressed in heart since the foetal stageand induce mycocardial hypertrophy through MAP-Kinases and PI-3 kinasepathways. IGF1 also stimulates myocardial protein production, includingsome with contractile functions such as troponine and actin. Therefore,IGF1 relates to cardiac contractile function and IGF1 levels arecorrelated to the left ventricular ejection fraction (LVEF). IGF1 isalso involved in cardiomyocytes survival and apoptosis. Murine modelsand also small clinical trials involving GH or IGF1 injection haverevealed a reduction of heart early remodeling, an improvement of thesystolic and diastolic function, and a contractility improvement.Recently, the addition of the neutralising IGFBP2 antibody upon celldifferentiation, led to an important myoblasts hypertrophy.

This study allowed us to analyze the link between HF and plasma IGFBP2and the potential use of IGFBP2 as a new biomarker. We clearly observedclose to a 7-fold rise in IGFBP2 plasmatic concentration in HF patients.Moreover, the test of IGFBP2 in the BNP “grey zone” revealed increaseddiscriminating power for this new biomarker.

IGFBP2 is mainly produced by the liver and the heart therefore is likelyto be indicative of liver or heart function. These points were evaluatedin the ischemic rat model of HF which also revealed a stronger IGFBP2mRNA level in atria vs ventricle or liver. Above all, IGFBP2 mRNA levelswere significantly increased in the atria from HF animals. Thisobservation raises the question of the putative role of IGFBP2 in atria.One could speculate that IGFP2 increased synthesis could be involved ina protective mechanism against excessive remodeling in heart becausereduction in vitro antibodies based neutralization of IGFBP2 uponmyoblasts differentiation led to hypertrophy 34. In addition,overexpression of IGFBP2 led to a reduction in muscle mass in the mouse36. However, despite solid backgrounds, this hypothesis will have to befurther tested in animals' models of HF.

Finally, we observed a significant negative correlation of the IGFBP2level with the LVEF value in patients. These observations tend topropose the use of IGFBP2 as a potential follow-up biomarker that couldbe used to estimate the stability and heart failure severity. However,because of its sensitivity and specificity in HF, the first use ofIGFBP2 could be in complementation with BNP in HF diagnosis in apopulation of patients with acute dyspnea form cardiac origin or not.

This study suffers from some limitations. The validation of the newIGFBP2 biomaker was performed with a small external cohort of patients.However, the rise of IGFBP2 concentration in AHF patients was reliableand qualifies IGFBP2 as a new biomarker. We now aim at testing IGFBP2 invery large multicentric international cohorts for further validations.Furthermore, the functional role of IGFBP2 in HF will be defined inrodent animal models.

The use of IGFBP2 as HF biomarker is promising and may improve HFdiagnostic especially in the BNP range of values indicative of mild tomoderate HF. Despite IGFBP2 synthesis is mainly produced by the heart,it is also secreted by the liver. This observation should not impair theuse of IGFBP2 for HF diagnosis. Clearly, HF is a syndrome and our datapropose that IGFBP2 is a reliable biomarker that could reveal the heartfunctional status.

REFERENCES

Throughout this application, various references describe the state ofthe art to which this invention pertains. The disclosures of thesereferences are hereby incorporated by reference into the presentdisclosure.

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1. A method for classifying a patient at risk for heart failure, whereinsaid method comprises the steps of: i. measuring the concentration ofIGFBP2 in a sample obtained from said patient, and ii. comparing theconcentration of IGFBP2 measured in step (i) to a control value derivedfrom the concentration of IGFBP2 in samples from patients who are atparticular stages of heart failure and/or to a control value derivedfrom the concentration of IGFBP2 in blood samples from healthy patients.2. A method for diagnosis of heart failure in a patient comprising: i.determining the concentration of IGFBP2 in a sample obtained from saidpatient; and ii. comparing said concentration to a control value.
 3. Themethod according to claim 1 wherein the heart failure is an asymptomaticheart failure, a chronic heart failure or an acute heart failure.
 4. Themethod according to claim 1, wherein said sample is selected in thegroup consisting of plasma and urine sample.
 5. The method according toclaim 1, wherein the concentration of IGFBP2 is measured by quantifyingthe level of IGFBP2 protein in the sample.
 6. The method according toclaim 5, wherein the quantification of the level of IGFBP2 protein isperformed by using a set of antibodies directed against IGFBP2.
 7. Themethod according to claim 5, wherein the quantification of the level ofIGFBP2 protein is performed by ELISA.
 8. The method according to claim5, wherein the quantification of the level of IGFBP2 protein isperformed by capillary electrophoresis-mass spectroscopy technique. 9.The method according to claim 2 wherein the heart failure is anasymptomatic heart failure, a chronic heart failure or an acute heartfailure.
 10. The method according to claim 2, wherein said sample isselected in the group consisting of plasma and urine sample.
 11. Themethod according to claim 2, wherein the concentration of IGFBP2 ismeasured by quantifying the level of IGFBP2 protein in the sample. 12.The method according to claim 11, wherein the quantification of thelevel of IGFBP2 protein is performed by using a set of antibodiesdirected against IGFBP2.
 13. The method according to claim 11, whereinthe quantification of the level of IGFBP2 protein is performed by ELISA.14. The method according to claim 11, wherein the quantification of thelevel of IGFBP2 protein is performed by capillary electrophoresis-massspectroscopy technique.